Therapeutic strategies and predictive models for Xp11.2 translocation/TFE3 gene fusion renal cell carcinoma in adults based on data of two Chinese medical centers

OBJECTIVE

This study aims to establish an effective predictive model for predicting Xp11.2 translocation/TFE3 gene fusion renal cell carcinoma (TFE3-RCC) and develop optimal therapeutic strategies.

METHODS

Data from 4961 patients diagnosed with renal cell carcinoma at two medical centers in China were retrospectively analyzed. A cohort of 1571 patients from Zhejiang Provincial People's Hospital (Ra cohort) was selected to construct the model. Another cohort of 1124 patients from the Second Affiliated Hospital of Zhejiang Chinese Medical University was used for external validation (the Ha cohort). All patients with TFE3-RCC in both cohorts were included in the Ta cohort for the prognostic analysis. Univariate and multivariate binary logistic regression analyses were performed to identify independent predictors of the predictive nomogram. The apparent performance of the model was validated. Decision curve analysis was also performed to assess the clinical utility of the developed model. Factors associated with progression and prognosis in the Ta cohort were analyzed using the log-rank method, and Cox regression analysis and Kaplan-Meier survival curves were used to describe the effects of factors on prognosis and progression.

RESULTS

Univariate and multivariate logistic regression analyses demonstrated that age, sex, BMI, smoking, eosinophils, and LDL were independent predictors of TFE3-RCC. Therefore, a predictive nomogram for TFE3-RCC, which had good discriminatory power (AUC = 0.796), was constructed. External validation (AUC = 0.806) also revealed good predictive ability. The calibration curves displayed good consistency between the predicted and observed incidences of TFE3-RCC. Invasion of regional lymph nodes, tyrosine kinase inhibitors, and surgical methods were independent factors associated with progression. Tyrosine kinase inhibitors are independent prognostic factors.

CONCLUSION

This study not only proposed a high-precision clinical prediction model composed of various variables for the early diagnosis of Xp11.2 translocation/TFE3 gene fusion renal cell carcinoma but also optimized therapeutic strategies through prognostic analysis.

High-throughput and targeted drug screens identify pharmacological candidates against MiT-translocation renal cell carcinoma

BACKGROUND

MiT-Renal Cell Carcinoma (RCC) is characterized by genomic translocations involving microphthalmia-associated transcription factor (MiT) family members TFE3, TFEB, or MITF. MiT-RCC represents a specific subtype of sporadic RCC that is predominantly seen in young patients and can present with heterogeneous histological features making diagnosis challenging. Moreover, the disease biology of this aggressive cancer is poorly understood and there is no accepted standard of care therapy for patients with advanced disease. Tumor-derived cell lines have been established from human TFE3-RCC providing useful models for preclinical studies.

METHODS

TFE3-RCC tumor derived cell lines and their tissues of origin were characterized by IHC and gene expression analyses. An unbiased high-throughput drug screen was performed to identify novel therapeutic agents for treatment of MiT-RCC. Potential therapeutic candidates were validated in in vitro and in vivo preclinical studies. Mechanistic assays were conducted to confirm the on-target effects of drugs.

RESULTS

The results of a high-throughput small molecule drug screen utilizing three TFE3-RCC tumor-derived cell lines identified five classes of agents with potential pharmacological efficacy, including inhibitors of phosphoinositide-3-kinase (PI3K) and mechanistic target of rapamycin (mTOR), and several additional agents, including the transcription inhibitor Mithramycin A. Upregulation of the cell surface marker GPNMB, a specific MiT transcriptional target, was confirmed in TFE3-RCC and evaluated as a therapeutic target using the GPNMB-targeted antibody-drug conjugate CDX-011. In vitro and in vivo preclinical studies demonstrated efficacy of the PI3K/mTOR inhibitor NVP-BGT226, Mithramycin A, and CDX-011 as potential therapeutic options for treating advanced MiT-RCC as single agents or in combination.

CONCLUSIONS

The results of the high-throughput drug screen and validation studies in TFE3-RCC tumor-derived cell lines have provided in vitro and in vivo preclinical data supporting the efficacy of the PI3K/mTOR inhibitor NVP-BGT226, the transcription inhibitor Mithramycin A, and GPNMB-targeted antibody-drug conjugate CDX-011 as potential therapeutic options for treating advanced MiT-RCC. The findings presented here should provide the basis for designing future clinical trials for patients with MiT-driven RCC.